Unified optimization of intelligent home appliances with a cost-effective energy management system
The scheduling in smart houses is a pivotal concern in power consumption networks on the demand side owing to the expanding usage of renewable energy resources (RERs). To address the issue of distributed energy management raised due to the expanded use of RERs, a peak-limiting distributed-time-boun...
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| Language: | English |
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OICC Press
2025-03-01
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| Series: | Majlesi Journal of Electrical Engineering |
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| Online Access: | https://oiccpress.com/mjee/article/view/10856 |
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| author | Vikas Deep Juyal Sandeep Kakran |
| author_facet | Vikas Deep Juyal Sandeep Kakran |
| author_sort | Vikas Deep Juyal |
| collection | DOAJ |
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The scheduling in smart houses is a pivotal concern in power consumption networks on the demand side owing to the expanding usage of renewable energy resources (RERs). To address the issue of distributed energy management raised due to the expanded use of RERs, a peak-limiting distributed-time-bound strategy is proposed and executed, providing a flexible distribution for the scheduling of appliances under real-time and time-of-use pricing schemes. This paper presents a case study based on the pilot project initiated in Gujarat, India, to better understand the scenario. The current work engenders a smart home energy management system harmonizing with a residential grid. By embracing the proposed methodology, the electricity cost can be curtailed to the bare minimum while concurrently reducing the peak demand, harnessing the maximum potential of renewable energy sources, and optimizing the peak-to-average ratio. Multiple scenarios have been enacted, encompassing various applicable tariff structures, methodologies, and the integration of renewable energy sources. The electricity bill using the proposed strategy is significantly reduced by about 95.25% compared to a random scheduling case (base case) considered in the paper. The maximum peak reduction
compared to the random scheduling case is about 70.8 % in one of the presented scenarios.
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| format | Article |
| id | doaj-art-c5b4703e0ef540918fb84f4af3edc6e7 |
| institution | OA Journals |
| issn | 2345-377X 2345-3796 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | OICC Press |
| record_format | Article |
| series | Majlesi Journal of Electrical Engineering |
| spelling | doaj-art-c5b4703e0ef540918fb84f4af3edc6e72025-08-20T01:55:58ZengOICC PressMajlesi Journal of Electrical Engineering2345-377X2345-37962025-03-01191 (March 2025)10.57647/j.mjee.2025.1901.07Unified optimization of intelligent home appliances with a cost-effective energy management systemVikas Deep Juyal0https://orcid.org/0000-0002-7516-6035Sandeep Kakran1https://orcid.org/0000-0003-2034-011XElectrical Engineering Department, National Institute of Technology Kurukshetra, IndiaElectrical Engineering Department, National Institute of Technology Kurukshetra, India The scheduling in smart houses is a pivotal concern in power consumption networks on the demand side owing to the expanding usage of renewable energy resources (RERs). To address the issue of distributed energy management raised due to the expanded use of RERs, a peak-limiting distributed-time-bound strategy is proposed and executed, providing a flexible distribution for the scheduling of appliances under real-time and time-of-use pricing schemes. This paper presents a case study based on the pilot project initiated in Gujarat, India, to better understand the scenario. The current work engenders a smart home energy management system harmonizing with a residential grid. By embracing the proposed methodology, the electricity cost can be curtailed to the bare minimum while concurrently reducing the peak demand, harnessing the maximum potential of renewable energy sources, and optimizing the peak-to-average ratio. Multiple scenarios have been enacted, encompassing various applicable tariff structures, methodologies, and the integration of renewable energy sources. The electricity bill using the proposed strategy is significantly reduced by about 95.25% compared to a random scheduling case (base case) considered in the paper. The maximum peak reduction compared to the random scheduling case is about 70.8 % in one of the presented scenarios. https://oiccpress.com/mjee/article/view/10856Cost-effective energy managementDemand responseHome energy managementRenewable energy source integrationDynamic pricingSmart home |
| spellingShingle | Vikas Deep Juyal Sandeep Kakran Unified optimization of intelligent home appliances with a cost-effective energy management system Majlesi Journal of Electrical Engineering Cost-effective energy management Demand response Home energy management Renewable energy source integration Dynamic pricing Smart home |
| title | Unified optimization of intelligent home appliances with a cost-effective energy management system |
| title_full | Unified optimization of intelligent home appliances with a cost-effective energy management system |
| title_fullStr | Unified optimization of intelligent home appliances with a cost-effective energy management system |
| title_full_unstemmed | Unified optimization of intelligent home appliances with a cost-effective energy management system |
| title_short | Unified optimization of intelligent home appliances with a cost-effective energy management system |
| title_sort | unified optimization of intelligent home appliances with a cost effective energy management system |
| topic | Cost-effective energy management Demand response Home energy management Renewable energy source integration Dynamic pricing Smart home |
| url | https://oiccpress.com/mjee/article/view/10856 |
| work_keys_str_mv | AT vikasdeepjuyal unifiedoptimizationofintelligenthomeapplianceswithacosteffectiveenergymanagementsystem AT sandeepkakran unifiedoptimizationofintelligenthomeapplianceswithacosteffectiveenergymanagementsystem |